Animal carcase analysis

ABSTRACT

The process for analyzing an ovine animal carcase comprises capturing an image of a dorsal view to generate color image data for the carcase ( 10 ). Predetermined anatomical points ( 21–24 ) of the carcase are identified to then derive dimensional measurements for the carcase. Also characterizing parameters such as yield and fat depth of the carcase are derived by processing color data included in the captured image data in conjunction with the derived dimensional measurements. The color data processed are the color data for predetermined selected surface areas, especially the chump, the loin and the shoulder areas ( 30–32 ) of the carcase ( 10 ) known or determined to have significant correlation to the characterizing parameter related to fatness. Desirably the tail ( 17 ) of the animal carcase is identified and its width determined since this is useful as a variable in a carcase yield predictive equation. The color data comprises average RGB values representing red, green and blue color components which are intensity normalized color values.

FIELD OF THE INVENTION

This invention relates to methods and apparatus for analysing animalcarcases, particularly for ovine carcase analyses.

BACKGROUND

In the meat industry, specialist trained and skilled operators areemployed, in abattoirs for example, in order to inspect each animalcarcase and to provide estimates or gradings of various parameters, suchas the predicted saleable meat yield of each carcase. Such predictionsof meat yield and gradings are very important for fixing a fair valuefor the carcase and for determining uses to which the carcase and meatcuts will be destined. Obviously it is very important for the meatindustry generally including producers, processors and consumers thatsuch operators are consistent both within a particular abattoir orprocessing facility and between different facilities at different placesand different times.

In the case of ovine carcases, particularly sheep carcases, the analysescommonly used include both quantitative and qualitative measurements orassessments such as dimensional measurements, yield, particularly “leanmeat yield”, and fat depths.

There have been proposed and developed automated systems for imagecapture and colour analysis for automating beef carcase yieldpredictions or gradings, or at least for providing some objectivereplacement or supplement to human operators. However, such automatedanalysis and yield predicting systems for beef have not been applicableto sheep carcases both in their physical construction and arrangement,and also in the analyses performed and data output.

OBJECT OF THE INVENTION

It is an object of the present invention to provide a method andapparatus for analysis of animal carcases, particularly ovine animalcarcases, so as to automatically derive quantitative and/or qualitativedescriptors or characteristics of the carcases.

SUMMARY OF THE INVENTION

According to one aspect of the present invention there is provided aprocess for analysing an animal carcase which includes the steps of:

providing an image capture means for capturing image data relating to ananimal carcase,

presenting an animal carcase to the image capture means, the carcasebeing positioned with the dorsal view of the carcase presented directlyto the image capture means,

capturing image data for the dorsal view of the carcase by the imagecapture means,

processing the image data so as to automatically identify predeterminedanatomical points of the carcase,

deriving dimensional measurements for the carcase by using theanatomical points identified, and

deriving at least one characterising parameter related to fatness of thecarcase by processing colour data included in the captured image data inconjunction with the derived dimensional measurements, the colour dataprocessed being the colour data for at least one predetermined selectedsurface area of the carcase known or determined to have a significantcorrelation to the characterising parameter related to fatness.

According to another aspect of the present invention there is providedan apparatus for analysing an animal carcase, the apparatus including:

image capture means for capturing image data relating to an animalcarcase, the image capture means including a colour camera located at animage capture station where an animal carcase is presented with thedorsal view of the carcase presented directly into the camera, the imagecapture means also including an associated system for converting thecamera video signals to digital colour data signals, and

processing means operative to automatically identify predeterminedanatomical points of the carcase by processing the digital colour datasignals, the processing means further being operative to derivedimensional measurements for the carcase using the anatomical pointsidentified, the processing means further being operative to derive atleast one characterising parameter related to fatness of the carcase byprocessing colour data included in the captured image data inconjunction with the derived dimensional measurements, the colour dataprocessed being the colour data for at least one predetermined selectedsurface area of the carcase known or determined to have a significantcorrelation to the characterising parameter related to fatness.

It will be convenient to describe the invention in relation to analysisof a sheep carcase but it is to be understood that other animal carcasescan be used with the present invention, particularly ovine carcasesincluding, for example, goat carcases. The particular sheep carcasesystem developed and to be described herein can be generally similar tosystems developed and published for analysing beef carcases, both interms of equipment and software. Therefore reference may be made to suchknown systems for general features of the sheep carcase system. Forexample, patent specification WO 91/14180 describes and illustrates abeef carcase analysis system providing principal components and systemsrequired for an automated analysis system.

As sheep carcases are typically less than half the length of beefcarcases, however, the appropriate mechanical components, whichgenerally means anything associated with the carcase imaging station canbe scaled down. Individual components such as the camera and a cameraenclosure (which preferably provides both physical protection and acontrolled environment for the camera can be substantially the same asin the beef carcase systems.

The preferred apparatus has the image capture means which includeslighting means for illuminating the regions of the carcase in the regionof the spine of the carcase where the predetermined selected surfaceareas of the carcase are located, the lighting means being positionedadjacent or distributed around the camera of the image capture means anddirected generally towards the dorsal aspect of the carcase presented.

With regard to lighting of the sheep carcases as they are presented tothe image capture means at the image capture station, it may besatisfactory to provide a single light source, e.g. adjacent to thecamera, to illuminate each sheep carcase presented for image capture. Asingle light source may be suitable since wider or more uniformillumination may not be necessary to identify the anatomical points andsince colour data used in the carcase analysis operation preferablyrelates to selected areas relatively close to the spine so thatillumination from a single light source adjacent the camera may providesufficient illumination for such areas. However it is also possible touse distributed lighting to give a flatter and more uniform lightdistribution.

Unlike beef carcases which are viewed as split sides with the lateralaspect presented to the camera, sheep carcases as mentioned earlier areimaged unsplit according to the present invention and are presented withthe dorsal view, i.e. the back of the carcase, presented directly to thecamera.

The analysis operations for sheep carcases are completely different tothose for beef carcases, resulting in a completely different set ofcarcase measurements and descriptors and, of course, the derived outputsfrom the system are completely different and are appropriate to thedescription of sheep carcases.

The image capture station is designed to provide an environment toenable accurate, repeatable positioning, illumination and image captureof the sheep carcases. It is designed so that carcases moving on thenormal abattoir carcase transport equipment progress unimpeded throughan enclosure or booth and the images are automatically acquired. Thecarcase transport equipment preferably includes alignment devicesoperative to ensure the sheep carcases are positioned with the dorsalview presented directly at the camera. The enclosure also includessensors to detect the presence of the carcases and control imagecapture.

The booth preferably includes its own lighting system to control theillumination of the carcase and the booth preferably excludes allexternal lighting so that external lighting does not illuminate thecarcase. The lighting arrangement may use light source(s) positionedadjacent or distributed around the camera to illuminate the regions ofthe carcase which are useful for indicating carcase fatness and to helpenhance the discrimination of fat and lean regions. Also included in thefield of view are standard coloured tiles which are used to calibratecolour measurements by compensating for any changes in illumination orcamera characteristics. The calibration procedures and apparatus can besubstantially the same as used for beef carcase systems and, inparticular, can be substantially as described in detail and illustratedin patent specification WO 98/39627.

For capturing the image data for each sheep carcase, the systempreferably uses a video camera. The video camera is preferably enclosedin a temperature controlled enclosure and generates standard formatvideo signals of the carcases which are provided to the controllingcomputer system. The camera and its enclosure can be substantially thesame as used for a beef carcase system and may be for example asdescribed in Australian patent specification No. PCT/AU00/00829, filed10 Jul. 2000.

The image capture system including the camera and associated computersystem may include a special interface card, known as a “frame grabber”to convert the camera video signals into a digital format. The imagedata will therefore comprise positional and colour data for each pixelin an array of pixels representing the imaged area. Once in a digitalformat, the sheep analysis software running on the computer system canprocess the image to detect features and make quantitative measurements.

The quantitative measurements can be generally grouped into twocategories:

-   -   (a) dimensional measurements, e.g. lengths, areas (including        lengths and/or areas of the entire carcase or of particular        components of the carcase such as the legs), ratios, angles,        etc.,    -   (b) colour measurements—for example each part of the captured        image may be converted into three values, i.e. the RGB values        representing the intensity of red, green and blue light coming        from each respective part of the carcase. The absolute and        relative values of these RGB numbers give a quantitative        representation of the colour of the parts of the carcase. If        desired, as described in patent specification No. PCT/AU00/00830        filed 10 Jul. 2000, the RGB values may be processed to provide        intensity normalised colour values, i.e. colour values        substantially independent of light intensity, so that subsequent        analyses using these intensity normalised colour values are not        subject to unwanted variations and inaccuracies due to differing        light intensities of the illuminating light source(s).

The computer system would in practice also provide an operator interfacefor the overall system to enable control, configuration and display ofresults to an operator. Operator input can be via conventionalperipheral devices such as via a computer mouse, keyboard, scanner, orvia electronic links to other abattoir computer systems.

BRIEF DESCRIPTION OF THE DRAWINGS

To describe and illustrate the analysis procedures reference will bemade to the accompanying drawings in which:

FIG. 1 shows a captured image of a sheep carcase suspended by the hindlegs, e.g. from an overhead rail in a conventional transport system ofan abattoir, the carcase having been presented to the camera with thedorsal view directly facing the camera.

FIG. 2 is a depiction of the image of FIG. 1 having been analysed toidentify and trace the carcase outline, to identify particularanatomical points, and to derive some dimensions,

FIG. 3 is a similar view showing predetermined areas of the carcaseidentified for colour based analyses, and

FIG. 4 is a flow chart showing the steps in the preferred processaccording to the present invention.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENT

As shown in the drawings, the captured image includes the image of thecarcase 10 against a background 11. The background may comprise theimage of a background panel such as a non-reflective black panel locatedbehind the carcase in the image capture booth. The illuminated carcaseoverlying the black background 11 will enable ready processing of theimage data to identify the outline 15 of the carcase image, e.g. byscanning inwardly from the edges 12 of the image through pixelsrepresenting the background 11 and identifying the boundary 15 by theabrupt change in colour and/or light intensity.

It may be possible for all dimensional measurements to be used in thesystem of the present invention to be measurements relating to theoutline, i.e. with no features internal to this outline being located,identified and measured. However, if desired, the system may beprogrammed and operated to analyse captured image data in the area ofthe rump 16 of the animal so as to identify the tail 17. As seen in thedrawings, the lateral edges of the tail 17 are delineated in thecaptured image by generally linear darker areas 18 extending lengthwisealong each side of the tail so that these linear darker areas 18 can beidentified by the analysis algorithms and hence the width of the tail 17can be determined for use in yield prediction as mentioned later.

The main aims of the dimensional analysis are to find shape descriptorsrelated to conformation/muscle score and also to locate features of thecarcase to enable determination of the positions of predetermined areasfor colour measurements and analysis.

FIG. 2 shows the results from locating the carcase outline 15 and theoverlaid lines 20 illustrate basic dimensional measurements. Allmeasurements are made with relation to detected “anatomical points”.These are points on the outline 15 which are readily detected byfeatures on the outline (e.g. sharp corners) and which are associatedwith particular parts of the anatomy. Examples are shown in FIG. 2 asthe head point 21, “elbows” 22, hips 23, leg outer points 24, and thegroin point 25. As well as simple linear distances as shown by the linesin FIG. 2, other measurements made may include: measurements of areasenclosed by the outline and various distance measurement lines 20;widths and areas on the hind legs 13 or portions thereof; and anglesbetween distance measurement lines, e.g. the groin angle 27 between thelines from the groin point 25 to the hind legs 13. Another measurementmentioned earlier is the width of the tail 17 which has been found tohave a significant predictive correlation to the yield of the carcaseand which can therefore be used as a variable in a yield predictiveequation.

The system may be calibrated so that dimensional measurements ordistances 20 in the image can be converted to true distances/areas onthe carcase by taking into account perspective or foreshortening effectsof the dorsal view used. These and other dimensional measurements canbeen mathematically related to carcase descriptions provided by expertgraders and also other quantitative measurements e.g. lean meat yieldand fat depths, so that the measurements can be used to predict theseother carcase descriptors in standardised manual carcase gradingsystems. Purely dimensional descriptors formerly provided by expertgraders can be readily calculated from the dimensional data derived fromthe image analysis by relatively simple geometrical formulae ortransformations. However, in deriving descriptors of the carcase such aslean meat yield, characteristics of the carcase in addition to purelydimensional characteristics are relevant and statistical methodologiescan be used to derive predictive equations utilising both dimensionaldata as well as colour related data shown to have good predictiverelationships or correlations with the descriptor being derived. Anexample of a purely dimensional characteristic having been determined tohave good predictive correlations with yield is the width or thicknessof the tail 17. Hence a derived measure of the width of the tail can beincorporated in a yield predictive equation.

With regard to utilising colour information in the captured image datato derive descriptors of the sheep carcase, the simplest method ofextracting colour information from the carcase image is to measure theaverage RGB values within a defined region. FIG. 3 shows rectangularareas superimposed on the carcase image. These rectangles have beenautomatically positioned relative to the anatomical features found inthe dimensional analysis (FIG. 2) and are designed to coincide withchump 30, loin 31 and shoulder areas 32 that carcase grading experts usefor evaluating carcase fatness. As illustrated, these areas 30–32 can bein respective pairs located symmetrically on opposite sides of thespine—enabling averaging of colour values for each laterally spacedpair, or possibly alarm or error signal generation if the average colourvalues for the two members of any pair vary significantly from eachother, enabling manual intervention to identify the cause and correctfor possible misleading output descriptors.

Relationships have been found by statistical analyses, e.g. multipleregression analyses, of multiple carcases to provide correlationsbetween average RGB values and carcase fatness. Alternative a methods ofusing the RGB values to predict fatness may also be developed, e.g.analysing the rate of change of RGB values in a line profile across thecarcase.

By discovering such relationships and providing the correlations todevelop predictive equations, the present invention can provide acarcase analysis process and apparatus which automatically determinesand outputs descriptors of the carcase, useful for example for gradingand valuing the carcases. As mentioned earlier, dimensional descriptorsare relatively easily derived and output once the outline and keyanatomical points have been determined from the captured carcase images.Other carcase descriptors such as lean meat yield and fat thickness arecorrelated not only to dimensional characteristics but also to colourcharacteristics and therefore the predictive equations for suchdescriptors can be derived by statistical techniques using bothdimensional and colour related parameters in the equations.

FIG. 4 illustrates process steps used in the processes according to thepreferred embodiments of the present invention for image capture andanalysis to provide characterising parameters for carcases. The stepscan be readily understood by reference to the preceding description.

It will be seen from the preceding description that the presentinvention provides a useful process and apparatus for animal carcaseanalysis, particularly for ovine animal carcase analysis enabling atleast partially automated analysis and output of useful carcasedescriptors.

1. A process for analysing an ovine animal carcase which includes thesteps of: providing an image capture means for capturing image datarelating to an ovine animal carcase, presenting an ovine animal carcaseto the image capture means, the carcase being positioned with the dorsalview of the carcase presented directly to the image capture means,capturing image data for the dorsal view of the carcase by the imagecapture means, processing the image data so as to automatically identifypredetermined anatomical points of the carcase, deriving dimensionalmeasurements for the carcase by using the anatomical points identified,and deriving at lease one characterising parameter related to fatness ofthe carcase by processing colour data included in the captured imagedata in conjunction with the derived dimensional measurements, thecolour data processed being the colour data for at least onepredetermined selected surface area of the carcase known or determinedto have a significant correlation to the characterising parameterrelated to fatness, wherein the process includes the further step ofprocessing the image data to identify the tail of the ovine animalcarcase, the identification of the tail comprising identification oflateral edges of the tail which are delineated in the captured image bygenerally linear darker areas extending lengthwise relative to the spineof the carcase, the process including the further step of determiningthe width of the tail between the lateral edges, and wherein the step ofderiving at least one characterising parameter includes deriving aparameter related to the predicted yield of the carcase using the widthof the tail as a variable in a carcase yield predictive equation.
 2. Aprocess as claimed in claim 1 wherein the step of processing colour datacomprises measuring the average RGB values representing red, green andblue color components within said at least one predetermined selectedsurface area.
 3. A process as claimed in claimed in claim 2 wherein theRGB values are intensity normalised colour values substantiallyindependent of light intensity.
 4. A process for analysing an ovineanimal carcase which includes the steps of: providing an image capturemeans for capturing image data relating to an ovine animal carcase,presenting an ovine animal carcase to the image capture means, thecarcase being positioned with the dorsal view of the carcase presenteddirectly to the image capture means, capturing image data for the dorsalview of the carcase by the image capture means, processing the imagedata so as to automatically identify predetermined anatomical points ofthe carcase, deriving dimensional measurements for the carcase by usingthe anatomical points identified, and deriving at least onecharacterising parameter related to fatness of the carcase by processingcolour data included in the captured image data in conjunction with thederived dimensional measurements, the colour data processed being thecolour data for at least one predetermined selected surface area of thecarcase known or determined to have a significant correlation to thecharacterising parameter related to fatness, the step of processingcolour data comprising measuring the average RGB values representingred, green and blue colour components within said at least onepredetermined selected surface area, wherein there are multiplepredetermined selected surface areas of the ovine animal carcase forwhich colour data is processed, the multiple predetermined surface areascomprising areas which are automatically positioned relative to thepredetermined anatomical points and which generally coincide with thechump, the loin and the shoulder areas of the ovine animal carcase usedin standardised manual carcase grading systems for evaluating carcasefatness.
 5. A process as claimed in claim 4 wherein the multiple surfaceareas are arranged in respective pairs locates symmetrically on oppositesides of the spine of the carcase, the processing of the coloured dataincluding averaging of colour values for each laterally spaced pair ofsurface areas.
 6. A process as claimed in claim 5 wherein the processingof colour data for the respective pairs of surface areas includescomparing the average colour values of each surface area with itsrespective counterpart of the respective pair and generating an alarm orerror signal if the average colour values for the two members of anypair vary significant from each other.
 7. A process for analysing ananimal carcase which includes the steps of: providing an image capturemeans for capturing image data relating to an animal carcase, presentingan animal carcase to the image capture means, the carcase beingpositioned with dorsal view of the carcase presented directly to theimage capture means, capturing image data for the dorsal view of thecarcase by the image capture means, processing the image data so as toautomatically identify predetermined anatomical points of the carcase,deriving at least one characterising parameter related to fatness of thecarcase by processing colour data included in the captured image date inconjunction with the derived dimensional measurements, the colour dataprocessed being the colour data for at least one predetermined selectedsurface area of the carcase known or determined to have a significantcorrelation to the characterising parameter related to fatness, the stepof processing colour data comprising measuring the average RGB valuesrepresenting red, green and blue color components within said at leastone predetermined selected surface area, wherein the step of processingthe colour data includes analysing the rate of change of RGB values in aline profile across the image of the carcase transverse to thelongitudinal line of the spine and wherein the step of deriving acharacterising parameter includes solving a predictive equation for ameasure of fatness of the carcase in which the rate of change of the RGBvalues is a variable in that predictive equation.
 8. A process foranalysing an animal carcase which includes the steps of: providing animage capture means for capturing image data relating to an animalcarcase, presenting an animal carcase to the image capture means, thecarcase being positioned with the dorsal view of the carcase presenteddirectly to the image capture means, capturing image data for the dorsalview of the carcase by the image capture means, processing the imagedata so as to automatically identify predetermined anatomical points ofthe carcase, deriving dimensional measurements for the carcase by usingthe anatomical points identified, and deriving at least onecharacterising parameter related to fatness of the carcase by processingcolour data included in the captured image data in conjunction with thederived dimensional measurements, the colour data processed being thecolour data for at least one predetermined selected surface area of thecarcase known or determined to have a significant correlation to thecharacterising parameter related to fatness, the step of processingcolour data comprises measuring the average RGB values representing red,green and blue colour components within said at least one predeterminedselected surface area, wherein the step of deriving a characterisingparameter related to fatness of the carcase includes performingstatistical analyses of multiple carcases to provide correlationsbetween average RGB values of said at least predetermined selectedsurface area and carcase fatness and using these correlations to developa predictive equation for carcase fatness in which the average RGBvalues are variables in the predictive equation.
 9. A process as claimedin claim 8 wherein the parameter related to fatness of the carcase isselected from lean meat yield and fat thickness.